Low-cost multi-spectral face imaging for robust face recognition

dc.contributor.author	Vetrekar, N.T.
dc.contributor.author	Raghavendra, R.
dc.contributor.author	Gad, R.S.
dc.date.accessioned	2016-11-15T09:28:05Z
dc.date.available	2016-11-15T09:28:05Z
dc.date.issued	2016
dc.identifier.citation	IEEE International Conference on Imaging Systems and Techniques (IST); 2016; 6pp.	en_US
dc.identifier.uri	http://dx.doi.org/10.1109/IST.2016.7738245
dc.identifier.uri	http://irgu.unigoa.ac.in/drs/handle/unigoa/4635
dc.description.abstract	Multi-spectral face recognition has acquired significant attention over a last few decades due to its potential of capturing spatial and spectral information across the electromagnetic spectrum. In this paper, we present a new imaging scheme that can obtain the multi-spectral face image at nine different spectra covering 530nm–1000nm. We prepared a new database comprising of 230 subjects using our new low-cost multi-spectral face imaging device. Extensive experiments are presented for evaluating the performance of the four different state-of-the-art face recognition algorithms on both individual bands and the fused spectral face image. Obtained results show the improved face recognition performance of Log-Gabor features with Collaborative Representation (CRC) as the classifier.
dc.publisher	IEEE	en_US
dc.subject	Electronics	en_US
dc.title	Low-cost multi-spectral face imaging for robust face recognition
dc.type	Conference article	en_US